%0 Conference Paper %1 MRNV2004 %A Giel, D. %A Frey, S. %A Thelen, A. %A Bongartz, J. %A Hering, P. %A Nüchter, A. %A Surmann, H. %A Lingemann, K. %A Hertzberg, J. %B Proceedings of the Scientific Workshop Medical Robotics, Navigation and Visualization (MRNV '04) %C Remagen, Germany %D 2004 %K imported myown %T Ultra-fast Holographic Recording and Automatic 3D Scan Matching of Living Human Faces %X 3D models of the skin surface of patients are created by ultra-fast holography and automatic scan matching of synchronously recorded holograms. By recording with a pulsed laser and continuous-wave optical reconstruction of the holographic real image, motion artifacts are eliminated. Focal analysis of the real image yields a surface relief of the patient. To generate a complete 360◦ patient model, several synchronously recorded reliefs are registered by automatic scan matching. We find the transformation consisting of a rotation and a translation that minimizes a cost function containing the Euclidian distances between points pairs from two surface relief maps. A variant of the ICP (Iterative Closest Points) algorithm is used to compute such a minimum. We propose a new fast approximation based on kD trees for the problem of creating the closest point pairs on which the ICP algorithm spends most of its time.

@inproceedings{MRNV2004, abstract = {3D models of the skin surface of patients are created by ultra-fast holography and automatic scan matching of synchronously recorded holograms. By recording with a pulsed laser and continuous-wave optical reconstruction of the holographic real image, motion artifacts are eliminated. Focal analysis of the real image yields a surface relief of the patient. To generate a complete 360◦ patient model, several synchronously recorded reliefs are registered by automatic scan matching. We find the transformation consisting of a rotation and a translation that minimizes a cost function containing the Euclidian distances between points pairs from two surface relief maps. A variant of the ICP (Iterative Closest Points) algorithm is used to compute such a minimum. We propose a new fast approximation based on kD trees for the problem of creating the closest point pairs on which the ICP algorithm spends most of its time.}, added-at = {2017-09-19T13:40:53.000+0200}, address = {Remagen, Germany}, author = {Giel, D. and Frey, S. and Thelen, A. and Bongartz, J. and Hering, P. and N\"{u}chter, A. and Surmann, H. and Lingemann, K. and Hertzberg, J.}, biburl = {https://www.bibsonomy.org/bibtex/2e917417bc82fe258af550e746276f8d6/nuechter76}, booktitle = {Proceedings of the Scientific Workshop Medical Robotics, Navigation and Visualization (MRNV '04)}, interhash = {962ab69891be919991ff083d388c0295}, intrahash = {e917417bc82fe258af550e746276f8d6}, keywords = {imported myown}, month = {March}, timestamp = {2021-09-10T19:33:05.000+0200}, title = {{Ultra-fast Holographic Recording and Automatic 3D Scan Matching of Living Human Faces}}, year = 2004 }